Abstract:&nbspStructural vector autoregressions (VARs) are widely used to trace out the effect of
monetary policy innovations on the economy. However, the sparse information sets
typically used in these empirical models lead to at least two potential problems with the
results. First, to the extent that central banks and the private sector have information not
reflected in the VAR, the measurement of policy innovations is likely to be contaminated.
A second problem is that impulse responses can be observed only for the included
variables, which generally constitute only a small subset of the variables that the
researcher and policymaker care about. In this paper we investigate one potential
solution to this limited information problem, which combines the standard structural
VAR analysis with recent developments in factor analysis for large data sets. We find
that the information that our factor-augmented VAR (FAVAR) methodology exploits is
indeed important to properly identify the monetary transmission mechanism. Overall, our
results provide a comprehensive and coherent picture of the effect of monetary policy on
the economy.